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Hajdu András

Hajdu András

Hajdu András
DE > IK
Komputergrafika és Képfeldolgozás Tanszék
egyetemi tanár, tanszékvezető 2008-
Név: Hajdu András
További profilok: Google Scholar, MTMT
Fokozat
  • PhD, Debreceni Egyetem (2003)
  • Habilitáció, Debreceni Egyetem (2008)
  • MTA doktora, MTA (2017)
Szakterület: matematikus, informatikus
Ajánlott linkek:
Önéletrajz: letöltés

Teljes publikációs lista

A lista áttöltése az MTMT rendszerébe
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Hitelesített Publikációs Lista igénylése
OA letöltési statisztika megtekintése
Feltöltött közlemény:
210
DEA-ban:
201
OA:
30
Publikációs időszak:
1997-2024
2024
  1. Lakatos, R., Bogacsovics, G., Harangi, B., Lakatos, I., Tiba, A., Tóth, J., Szabó, M., Hajdu, A.: A Machine Learning-Based Pipeline for the Extraction of Insights from Customer Reviews.
    Big Data Cogn. Comput. 8 (3), 1-24, 2024.
    Folyóirat-mutatók:
    Q2 Artificial Intelligence (2022)
    Q2 Computer Science Applications (2022)
    Q2 Information Systems (2022)
    Q2 Management Information Systems (2022)
2023
  1. Gombos, B., Nagy, Z., Hajdu, A., Nagy, J.: Climate change in the Debrecen area in the last 50 years and its impact on maize production.
    Idojaras. 127 (4), 485-504, 2023.
    Folyóirat-mutatók:
    Q4 Atmospheric Science (2022)
  2. Harangi, B., Baran, Á., Beregi-Kovács, M., Hajdu, A.: Composing Diverse Ensembles of Convolutional Neural Networks by Penalization.
    Mathematics. 11 (23), 1-19, 2023.
    Folyóirat-mutatók:
    Q2 Computer Science (miscellaneous) (2022)
    Q2 Engineering (miscellaneous) (2022)
    Q2 Mathematics (miscellaneous) (2022)
  3. Pándy, Á., Harangi, B., Hajdu, A.: Extracting Drug Names from Medical Reports.
    In: IEEE 18th International Conference on Computer Science and Information Technologies (CSIT), IEEE, Piscataway, 1-4, 2023. ISBN: 9798350360462
  4. Bogacsovics, G., Harangi, B., Hajdu, A.: Increasing the diversity of ensemble members for accurate brain tumor classification.
    In: 36th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2023, Institute of Electrical and Electronics Engineers Inc., [s.l.], 529-534, 2023. ISBN: 9798350312249
  5. Liu, Y., Zhou, S., Wang, L., Xu, M., Huang, X., Li, Z., Hajdu, A., Zhang, L.: Machine learning approach combined with causal relationship inferring unlocks the shared pathomechanism between COVID-19 and acute myocardial infarction.
    Front. Microbiol. 14 1-10, 2023.
    Folyóirat-mutatók:
    Q1 Microbiology (2022)
    Q1 Microbiology (medical) (2022)
  6. Pándy, Á., Kovács, L., Kovács, Á., Hajdu, A.: Steering Angle Prediction From a Camera Image as a Backup Service.
    IEEE Sens. Lett. 7 (11), 1-4, 2023.
    Folyóirat-mutatók:
    Q2 Electrical and Electronic Engineering (2022)
    Q2 Instrumentation (2022)
  7. Tóth, J., Tomán, H., Hajdu, G., Hajdu, A.: Using Noisy Evaluation to Accelerate Parameter Optimization of Medical Image Segmentation Ensembles.
    Mathematics. 11 (18), 1-17, 2023.
    Folyóirat-mutatók:
    Q2 Computer Science (miscellaneous) (2022)
    Q2 Engineering (miscellaneous) (2022)
    Q2 Mathematics (miscellaneous) (2022)
2022
  1. Kapusi, T., Erdei, T., Husi, G., Hajdu, A.: Application of Deep Learning in the Deployment of an Industrial SCARA Machine for Real-Time Object Detection.
    Robotics. 11 (4), 1-20, 2022.
    Folyóirat-mutatók:
    Q2 Artificial Intelligence
    Q1 Control and Optimization
    Q1 Mechanical Engineering
  2. Hajdu, A., Terdik, G., Tiba, A., Tomán, H.: A stochastic approach to handle resource constraints as knapsack problems in ensemble pruning.
    Mach. Learn. 111 1551-1595, 2022.
    Folyóirat-mutatók:
    Q1 Artificial Intelligence
    Q1 Software
  3. Huang, X., Zhou, S., Tóth, J., Hajdu, A.: Cuproptosis-related gene index: a predictor for pancreatic cancer prognosis, immunotherapy efficacy, and chemosensitivity.
    Front. Immunol. 13 1-31, 2022.
    Folyóirat-mutatók:
    Q1 Immunology
    Q1 Immunology and Allergy
  4. Kapusi, T., Kovács, L., Hajdu, A.: Deep learning-based anomaly detection for imaging in autonomous vehicles.
    In: 2022 IEEE 2nd Conference on Information Technology and Data Science (CITDS): Proceedings (2022.05.16-18.)(Debrecen). Szerk.: Fazekas István, IEEE, Piscataway (NJ), 142-147, 2022. ISBN: 9781665496520
  5. Bogacsovics, G., Tóth, J., Hajdu, A., Harangi, B.: Enhancing CNNs through the use of hand-crafted features in automated fundus image classification.
    Biomed. Signal Process. Control. 76 1-10, 2022.
    Folyóirat-mutatók:
    Q1 Biomedical Engineering
    Q1 Health Informatics
    Q1 Signal Processing
  6. Pándy, Á., Kun, D., Kovács, L., Vasváry, G., Pánti, Z., Hajdu, A.: Image sensor based steering signal for a digital actuator system.
    In: 2022 IEEE 2nd Conference on Information Technology and Data Science (CITDS) / Fazekas István, IEEE, Piscataway, 229-234, 2022. ISBN: 9781665496537
  7. Lakatos, R., Bogacsovics, G., Hajdu, A.: Predicting the direction of the oil price trend using sentiment analysis.
    In: IEEE 2nd Conference on Information Technology and Data Science (CITDS) : Proceedings. Ed.: Fazekas István, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, 177-182, 2022.
2021
  1. Bogacsovics, G., Hajdu, A., Harangi, B.: Cell Segmentation in Digitized Pap Smear Images Using an Ensemble of Fully Convolutional Networks.
    In: 2021 IEEE Signal Processing in Medicine and Biology Symposium : Proceedings, IEEE, Philadelphia, 1-6, 2021. ISBN: 9781665428972
  2. Lantang, O., Terdik, G., Hajdu, A., Tiba, A.: Comparison of single and ensemble-based convolutional neural networks for cancerous image classification.
    Ann. Math. Inform. 54 45-56, 2021.
    Folyóirat-mutatók:
    Q3 Computer Science (miscellaneous)
    Q4 Mathematics (miscellaneous)
  3. Ahammed, A., Harangi, B., Hajdu, A.: Hybrid AdaBoost and Naïve Bayes classifier for supervised learning.
    In: Proceedings of the 1st Conference on Information Technology and Data Science. Ed.: István Fazekas, András Hajdu, Tibor Tómács, CEUR Workshop Proceedings, Debrecen, 1-18, 2021, (CEUR Workshop Proceedings, ISSN 1613-0073 ; 2874.)
  4. Lantang, O., Terdik, G., Hajdu, A., Tiba, A.: Investigation of the efficiency of an interconnected convolutional neural network by classifying medical images.
    Ann. Math. Inform. 53 219-234, 2021.
    Folyóirat-mutatók:
    Q3 Computer Science (miscellaneous)
    Q4 Mathematics (miscellaneous)
  5. Lakatos, I., Hajdu, A., Harangi, B.: Molecule Classification Using Visualization and Convolutional Neural Network.
    In: IEEE 18th International Symposium on Biomedical Imaging (ISBI), IEEE, Piscataway, 1695-1698, 2021.
Mindet mutasd
frissítve: 2024-03-02, 01:41

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